Thirty-day re-hospitalizations disproportionately impact African American patients and those from socioeconomically disadvantaged neighborhoods. Hospitals that primarily serve disadvantaged populations bear a disproportionate burden of Medicare's hospital-based financial re-hospitalization penalties (mandated by S. 3025, Affordable Care Act). As these penalties continue to increase in coming years, penalized hospitals have stated that they will need to cut services to maintain financial solvency, which may further worsen disparities. This may be a potential unintended negative consequence of Medicare's policy decision to not adjust for socioeconomic factors in the re-hospitalization metrics to which the penalties are tied. At this decision's core is a debate on whether observed disparities result from confounding by cluster (i.e., disadvantaged populations primarily receiving care from 'bad' hospitals) or whether socioeconomic disadvantage outside the hospital has a greater influence on re-hospitalization than is currently recognized by Medicare. A statistical decomposition of the within- and between- hospital effects is needed to help disentangle whether the hospital or non-hospital socioeconomics play the greater role in re-hospitalization, but until recently few national-scale indictors of disadvantage were available for this purpose. (Individual-level indicators of disadvantage are neither widely available nor reliabl enough for either resolving this debate or for use in metric adjustment.) The Area Deprivation Index (ADI) is a validated measure of US disadvantage, based upon similar measures employed abroad for health policy development. The ADI uses US Census poverty, education, and housing and employment indicators to characterize regions, such as neighborhoods. Recently, we demonstrated that living in a severely disadvantaged US neighborhood (per a year 2000 Census-based ADI) predicts re-hospitalization as powerfully as the presence of illnesses, such as chronic pulmonary disease. However, to answer the critical policy debate above and to understand if the ADI is suitable for use as a metric adjuster, the ADI must be updated to the 2010 Census, its geographic stability (i.e., how the distribution of disadvantaged US neighborhoods has changed since 2000) and association consistency (i.e., whether the association of neighborhood disadvantage and re-hospitalization remains in 2010) determined, within- and between-hospital effects assessed (i.e., informing the hospital vs. neighborhood socioeconomics debate), and resilient hospitals (i.e., hospitals which primarily serve highly disadvantaged neighborhoods yet have lower than expected re-hospitalization rates) studied in comparison to less-resilient/non-resilient hospitals, especially in terms of patient, caregiver and clinician perspectives on the underlying reasons for this resilience. The potential policy impact o metric adjustment must also be understood. We propose to accomplish all of these steps, with an overarching goal of eliminating re-hospitalization disparities by informing policy and practice. This proposed project has the potential to immediately change re-hospitalization policy and inform metric revision.